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Academic Journal

Improving the explainability of autoencoder factors for commodities through forecast-based Shapley values.

Authors : Cerqueti, Roy^1,2 ; Iovanella, Antonio³; Mattera, Raffaele¹

Source: Scientific Reports. 8/23/2024, Vol. 14 Issue 1, p1-13. 13p.

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Simulating clinical features on chest radiographs for medical image exploration and CNN explainability using a style-based generative adversarial autoencoder.

Authors : Hasenstab, Kyle A.^1,2 (AUTHOR) ; Hahn, Lewis² (AUTHOR); Chao, Nick¹ (AUTHOR)

Source: Scientific Reports. 10/18/2024, Vol. 14 Issue 1, p1-12. 12p.

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基于多要素的短临降水预报及可解释性分析.

Authors : 陈龙¹ ; 彭静¹; 胡雪飞¹

Source: Application Research of Computers / Jisuanji Yingyong Yanjiu. Sep2024, Vol. 41 Issue 9, p2773-2780. 8p.

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Automated Sensor Node Malicious Activity Detection with Explainability Analysis.

Authors : Zubair, Md¹ (AUTHOR) ; Janicke, Helge² (AUTHOR) ; Mohsin, Ahmad² (AUTHOR)

Source: Sensors (14248220). Jun2024, Vol. 24 Issue 12, p3712. 24p.

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Generative Adversarial Networks for SAR Automatic Target Recognition and Classification Models Enhanced Explainability: Perspectives and Challenges.

Authors : Remusati, Héloïse¹ (AUTHOR) ; Le Caillec, Jean-Marc² (AUTHOR) ; Schneider, Jean-Yves¹ (AUTHOR)

Source: Remote Sensing. Jul2024, Vol. 16 Issue 14, p2569. 33p.

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Saliency-driven explainable deep learning in medical imaging: bridging visual explainability and statistical quantitative analysis.

Authors : Brima, Yusuf¹ (AUTHOR) ; Atemkeng, Marcellin² (AUTHOR)

Source: BioData Mining. 6/22/2024, Vol. 17 Issue 1, p1-33. 33p.

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Reproducibility and Explainability of Deep Learning in Mammography: A Systematic Review of Literature.

Authors : Bhalla, Deeksha¹ (AUTHOR); Rangarajan, Krithika¹ (AUTHOR) ; Chandra, Tany¹ (AUTHOR)

Source: Indian Journal of Radiology & Imaging. Jul2024, Vol. 34 Issue 3, p469-487. 19p.

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Machine Learning-Based Uranium Prospectivity Mapping and Model Explainability Research.

Authors : Kong, Weihao^1,2,3 (AUTHOR) ; Chen, Jianping^1,2 (AUTHOR) ; Zhu, Pengfei³ (AUTHOR)

Source: Minerals (2075-163X). Feb2024, Vol. 14 Issue 2, p128. 20p.

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Unlocking the black box: analysing the EU artificial intelligence act's framework for explainability in AI.

Authors : Pavlidis, Georgios¹ (AUTHOR)

Source: Law, Innovation & Technology. May2024, Vol. 16 Issue 1, p293-308. 16p.

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Novel rockburst prediction criterion with enhanced explainability employing CatBoost and nature-inspired metaheuristic technique.

Authors : Yingui Qiu¹; Jian Zhou¹

Source: Underground Space (2096-2754). Dec2024, Vol. 19, p101-118. 18p.

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فلترة النتائج

Improving the explainability of autoencoder factors for commodities through forecast-based Shapley values.

Simulating clinical features on chest radiographs for medical image exploration and CNN explainability using a style-based generative adversarial autoencoder.

基于多要素的短临降水预报及可解释性分析.

Automated Sensor Node Malicious Activity Detection with Explainability Analysis.

Generative Adversarial Networks for SAR Automatic Target Recognition and Classification Models Enhanced Explainability: Perspectives and Challenges.

Saliency-driven explainable deep learning in medical imaging: bridging visual explainability and statistical quantitative analysis.

Reproducibility and Explainability of Deep Learning in Mammography: A Systematic Review of Literature.

Machine Learning-Based Uranium Prospectivity Mapping and Model Explainability Research.

Unlocking the black box: analysing the EU artificial intelligence act's framework for explainability in AI.

Novel rockburst prediction criterion with enhanced explainability employing CatBoost and nature-inspired metaheuristic technique.

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